import logging import os from six.moves import xrange from kafka import SimpleConsumer, MultiProcessConsumer, KafkaConsumer, create_message from kafka.common import ( ProduceRequest, ConsumerFetchSizeTooSmall, ConsumerTimeout ) from kafka.consumer.base import MAX_FETCH_BUFFER_SIZE_BYTES from test.fixtures import ZookeeperFixture, KafkaFixture from test.testutil import ( KafkaIntegrationTestCase, kafka_versions, random_string, Timer ) class TestConsumerIntegration(KafkaIntegrationTestCase): @classmethod def setUpClass(cls): if not os.environ.get('KAFKA_VERSION'): return cls.zk = ZookeeperFixture.instance() cls.server1 = KafkaFixture.instance(0, cls.zk.host, cls.zk.port) cls.server2 = KafkaFixture.instance(1, cls.zk.host, cls.zk.port) cls.server = cls.server1 # Bootstrapping server @classmethod def tearDownClass(cls): if not os.environ.get('KAFKA_VERSION'): return cls.server1.close() cls.server2.close() cls.zk.close() def send_messages(self, partition, messages): messages = [ create_message(self.msg(str(msg))) for msg in messages ] produce = ProduceRequest(self.topic, partition, messages = messages) resp, = self.client.send_produce_request([produce]) self.assertEqual(resp.error, 0) return [ x.value for x in messages ] def assert_message_count(self, messages, num_messages): # Make sure we got them all self.assertEqual(len(messages), num_messages) # Make sure there are no duplicates self.assertEqual(len(set(messages)), num_messages) def consumer(self, **kwargs): if os.environ['KAFKA_VERSION'] == "0.8.0": # Kafka 0.8.0 simply doesn't support offset requests, so hard code it being off kwargs['auto_commit'] = False else: kwargs.setdefault('auto_commit', True) consumer_class = kwargs.pop('consumer', SimpleConsumer) group = kwargs.pop('group', self.id().encode('utf-8')) topic = kwargs.pop('topic', self.topic) if consumer_class == SimpleConsumer: kwargs.setdefault('iter_timeout', 0) return consumer_class(self.client, group, topic, **kwargs) def kafka_consumer(self, **configs): brokers = '%s:%d' % (self.server.host, self.server.port) consumer = KafkaConsumer(self.topic, metadata_broker_list=brokers, **configs) return consumer @kafka_versions("all") def test_simple_consumer(self): self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) # Start a consumer consumer = self.consumer() self.assert_message_count([ message for message in consumer ], 200) consumer.stop() @kafka_versions("all") def test_simple_consumer__seek(self): self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) consumer = self.consumer() # Rewind 10 messages from the end consumer.seek(-10, 2) self.assert_message_count([ message for message in consumer ], 10) # Rewind 13 messages from the end consumer.seek(-13, 2) self.assert_message_count([ message for message in consumer ], 13) consumer.stop() @kafka_versions("all") def test_simple_consumer_blocking(self): consumer = self.consumer() # Ask for 5 messages, nothing in queue, block 5 seconds with Timer() as t: messages = consumer.get_messages(block=True, timeout=5) self.assert_message_count(messages, 0) self.assertGreaterEqual(t.interval, 5) self.send_messages(0, range(0, 10)) # Ask for 5 messages, 10 in queue. Get 5 back, no blocking with Timer() as t: messages = consumer.get_messages(count=5, block=True, timeout=5) self.assert_message_count(messages, 5) self.assertLessEqual(t.interval, 1) # Ask for 10 messages, get 5 back, block 5 seconds with Timer() as t: messages = consumer.get_messages(count=10, block=True, timeout=5) self.assert_message_count(messages, 5) self.assertGreaterEqual(t.interval, 5) consumer.stop() @kafka_versions("all") def test_simple_consumer_pending(self): # make sure that we start with no pending messages consumer = self.consumer() self.assertEquals(consumer.pending(), 0) self.assertEquals(consumer.pending(partitions=[0]), 0) self.assertEquals(consumer.pending(partitions=[1]), 0) # Produce 10 messages to partitions 0 and 1 self.send_messages(0, range(0, 10)) self.send_messages(1, range(10, 20)) consumer = self.consumer() self.assertEqual(consumer.pending(), 20) self.assertEqual(consumer.pending(partitions=[0]), 10) self.assertEqual(consumer.pending(partitions=[1]), 10) # move to last message, so one partition should have 1 pending # message and other 0 consumer.seek(-1, 2) self.assertEqual(consumer.pending(), 1) pending_part1 = consumer.pending(partitions=[0]) pending_part2 = consumer.pending(partitions=[1]) self.assertEquals(set([0, 1]), set([pending_part1, pending_part2])) consumer.stop() @kafka_versions("all") def test_multi_process_consumer(self): # Produce 100 messages to partitions 0 and 1 self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) consumer = self.consumer(consumer = MultiProcessConsumer) self.assert_message_count([ message for message in consumer ], 200) consumer.stop() @kafka_versions("all") def test_multi_process_consumer_blocking(self): consumer = self.consumer(consumer = MultiProcessConsumer) # Ask for 5 messages, No messages in queue, block 5 seconds with Timer() as t: messages = consumer.get_messages(block=True, timeout=5) self.assert_message_count(messages, 0) self.assertGreaterEqual(t.interval, 5) # Send 10 messages self.send_messages(0, range(0, 10)) # Ask for 5 messages, 10 messages in queue, block 0 seconds with Timer() as t: messages = consumer.get_messages(count=5, block=True, timeout=5) self.assert_message_count(messages, 5) self.assertLessEqual(t.interval, 1) # Ask for 10 messages, 5 in queue, block 5 seconds with Timer() as t: messages = consumer.get_messages(count=10, block=True, timeout=5) self.assert_message_count(messages, 5) self.assertGreaterEqual(t.interval, 4.95) consumer.stop() @kafka_versions("all") def test_multi_proc_pending(self): self.send_messages(0, range(0, 10)) self.send_messages(1, range(10, 20)) consumer = MultiProcessConsumer(self.client, "group1", self.topic, auto_commit=False) self.assertEqual(consumer.pending(), 20) self.assertEqual(consumer.pending(partitions=[0]), 10) self.assertEqual(consumer.pending(partitions=[1]), 10) consumer.stop() @kafka_versions("all") def test_large_messages(self): # Produce 10 "normal" size messages small_messages = self.send_messages(0, [ str(x) for x in range(10) ]) # Produce 10 messages that are large (bigger than default fetch size) large_messages = self.send_messages(0, [ random_string(5000) for x in range(10) ]) # Consumer should still get all of them consumer = self.consumer() expected_messages = set(small_messages + large_messages) actual_messages = set([ x.message.value for x in consumer ]) self.assertEqual(expected_messages, actual_messages) consumer.stop() @kafka_versions("all") def test_huge_messages(self): huge_message, = self.send_messages(0, [ create_message(random_string(MAX_FETCH_BUFFER_SIZE_BYTES + 10)), ]) # Create a consumer with the default buffer size consumer = self.consumer() # This consumer failes to get the message with self.assertRaises(ConsumerFetchSizeTooSmall): consumer.get_message(False, 0.1) consumer.stop() # Create a consumer with no fetch size limit big_consumer = self.consumer( max_buffer_size = None, partitions = [0], ) # Seek to the last message big_consumer.seek(-1, 2) # Consume giant message successfully message = big_consumer.get_message(block=False, timeout=10) self.assertIsNotNone(message) self.assertEqual(message.message.value, huge_message) big_consumer.stop() @kafka_versions("0.8.1", "0.8.1.1", "0.8.2.0") def test_offset_behavior__resuming_behavior(self): self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) # Start a consumer consumer1 = self.consumer( auto_commit_every_t = None, auto_commit_every_n = 20, ) # Grab the first 195 messages output_msgs1 = [ consumer1.get_message().message.value for _ in xrange(195) ] self.assert_message_count(output_msgs1, 195) # The total offset across both partitions should be at 180 consumer2 = self.consumer( auto_commit_every_t = None, auto_commit_every_n = 20, ) # 181-200 self.assert_message_count([ message for message in consumer2 ], 20) consumer1.stop() consumer2.stop() # TODO: Make this a unit test -- should not require integration @kafka_versions("all") def test_fetch_buffer_size(self): # Test parameters (see issue 135 / PR 136) TEST_MESSAGE_SIZE=1048 INIT_BUFFER_SIZE=1024 MAX_BUFFER_SIZE=2048 assert TEST_MESSAGE_SIZE > INIT_BUFFER_SIZE assert TEST_MESSAGE_SIZE < MAX_BUFFER_SIZE assert MAX_BUFFER_SIZE == 2 * INIT_BUFFER_SIZE self.send_messages(0, [ "x" * 1048 ]) self.send_messages(1, [ "x" * 1048 ]) consumer = self.consumer(buffer_size=1024, max_buffer_size=2048) messages = [ message for message in consumer ] self.assertEqual(len(messages), 2) @kafka_versions("all") def test_kafka_consumer(self): self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) # Start a consumer consumer = self.kafka_consumer(auto_offset_reset='smallest', consumer_timeout_ms=5000) n = 0 messages = {0: set(), 1: set()} logging.debug("kafka consumer offsets: %s" % consumer.offsets()) for m in consumer: logging.debug("Consumed message %s" % repr(m)) n += 1 messages[m.partition].add(m.offset) if n >= 200: break self.assertEqual(len(messages[0]), 100) self.assertEqual(len(messages[1]), 100) @kafka_versions("all") def test_kafka_consumer__blocking(self): TIMEOUT_MS = 500 consumer = self.kafka_consumer(auto_offset_reset='smallest', consumer_timeout_ms=TIMEOUT_MS) # Ask for 5 messages, nothing in queue, block 5 seconds with Timer() as t: with self.assertRaises(ConsumerTimeout): msg = consumer.next() self.assertGreaterEqual(t.interval, TIMEOUT_MS / 1000.0 ) self.send_messages(0, range(0, 10)) # Ask for 5 messages, 10 in queue. Get 5 back, no blocking messages = set() with Timer() as t: for i in range(5): msg = consumer.next() messages.add((msg.partition, msg.offset)) self.assertEqual(len(messages), 5) self.assertLess(t.interval, TIMEOUT_MS / 1000.0 ) # Ask for 10 messages, get 5 back, block 5 seconds messages = set() with Timer() as t: with self.assertRaises(ConsumerTimeout): for i in range(10): msg = consumer.next() messages.add((msg.partition, msg.offset)) self.assertEqual(len(messages), 5) self.assertGreaterEqual(t.interval, TIMEOUT_MS / 1000.0 ) @kafka_versions("0.8.1", "0.8.1.1", "0.8.2.0") def test_kafka_consumer__offset_commit_resume(self): GROUP_ID = random_string(10) self.send_messages(0, range(0, 100)) self.send_messages(1, range(100, 200)) # Start a consumer consumer1 = self.kafka_consumer( group_id = GROUP_ID, auto_commit_enable = True, auto_commit_interval_ms = None, auto_commit_interval_messages = 20, auto_offset_reset='smallest', ) # Grab the first 195 messages output_msgs1 = [] for _ in xrange(195): m = consumer1.next() output_msgs1.append(m) consumer1.task_done(m) self.assert_message_count(output_msgs1, 195) # The total offset across both partitions should be at 180 consumer2 = self.kafka_consumer( group_id = GROUP_ID, auto_commit_enable = True, auto_commit_interval_ms = None, auto_commit_interval_messages = 20, consumer_timeout_ms = 100, auto_offset_reset='smallest', ) # 181-200 output_msgs2 = [] with self.assertRaises(ConsumerTimeout): while True: m = consumer2.next() output_msgs2.append(m) self.assert_message_count(output_msgs2, 20) self.assertEqual(len(set(output_msgs1) & set(output_msgs2)), 15)